Track Topology Research Articles

Robust Artificial Intelligence-Aided Multimodal Rail-Obstacle Detection Method by Rail Track Topology Reconstruction

Detecting obstacles in the rail track area is crucial for ensuring the safe operation of trains. However, this task presents numerous challenges, including the diverse nature of intrusions, and the complexity of the driving environment. This paper presents a multimodal fusion rail-obstacle detection approach by key points processing and rail track topology reconstruction. The core idea is to leverage the rich semantic information provided by images to design algorithms for reconstructing the topological structure of railway tracks. Additionally, it combines the effective geometric information provided by LiDAR to accurately locate the railway tracks in space and to filter out intrusions within the track area. Experimental results demonstrate that our method outperforms other approaches with a longer effective working distance and superior accuracy. Furthermore, our post-processing method exhibits robustness even under extreme weather conditions.

A Modified DDQ Track for Interoperable EV Dynamic Charging

The design and realization of dynamic EV charging systems face challenges such as large coupling variations and interoperability requirements. The study of the dynamic process using exhaustive simulation approaches is also time-consuming. This paper proposes a two-phase DDQ track topology focusing on improving interoperability and reducing power transfer fluctuations. A method to simplify the design process is also presented. By converting the dynamic procedure of a multi-coil system into a mathematical model of a single-coil to single-coil system, the method simplifies the evaluation of numerous designs into a calculation script associated with a much lower simulation count. Analysis and evaluations based on coupling profile, interoperability, and cost-effectiveness are carried out from both general and statistical points of view. A design that meets minimum misalignment requirements and has a stable coupling profile is selected for prototyping. The experiment at a 10-kW power level verifies the simulation and analysis.

Reconstruction of missing data of the PandaX-IIIexperiment TPC using neural network

The PandaX-III is a Neutrinoless Double-Beta Decay (NLDBD) experiment which uses a Time Projection Chamber (TPC) detector with a readout plane formed of Micromegas modules, which allows reconstruction of track topology for the background discrimination as well as reconstruction of the energy of the events. In NLDBD experiments, in order to achieve the highest sensitivity to the decay, it is necessary for the detector to have a high energy resolution, the background level should be low, and techniques for background discrimination must be applied as well. In reality, inhomogeneous signal gain at each module and the presence of missing channels lead to an incorrect energy reconstruction of the events. In this work, a method based on a Convolutional Neural Networks (CNN) aiming to reconstruct the kinematics of the event from imperfect data with missing channels is presented. Preliminary results of the reconstruction of the missing data using CNN are showing an increase in detection efficiency. The detection efficiency was evaluated on the simulated data with three channels randomly chosen per Micromegas module and artificially set as missing. Direct reconstruction of the energy gives the efficiency of 78%, while after applying CNN it increases to 86%, providing a promising application of this technique.

Permanent Magnet Electrodynamic Suspensions Applied to MAGLEV Transportation Systems: A Review

This article reviews permanent magnet electrodynamic suspensions (PM-EDSs) used in ground transportation systems, such as Magnetic Levitation (MAGLEV) trains. The different suspension topologies are first presented, considering separately their two main components, namely the track and the magnetic field source. Beyond that, a phenomenological explanation of the evolution with the speed of the drag and levitation forces is provided, depending on the track topology. The models aimed at predicting the behavior and performance of the suspension are then detailed, classifying them according to whether they are global or local. Finally, the main experimental setups developed to validate PM-EDSs are described.

Feasibility of solar tracking and fixed topologies considering the estimated degradation and performance of photovoltaic panels

Solar tracking maximizes the amount of electricity generated by photovoltaic (PV) panels throughout the day. Nevertheless, it is necessary to understand the effects of the topology on the degradation of PV modules. Thus, a methodology is described in this paper to predict changes in the degradation and performance over the lifetime of PV panels according to solar tracking topology. A technical and economic analysis of an experimental system built in UFSM (Santa Maria-RS, Brazil) is used to discuss typical configurations with and without solar tracking. Computational simulations were performed in the OpenDSS, Matlab and Homer programs for a period of 25 years. The results show an increase up to 2.43% in the accumulated degradation at the end of the simulated period by using a solar panel tracking compared to the fixed topology. In compensation, solar tracking increased annual electricity generation by an average of 20.87% proving that this topology is technically and economically quite feasible. • A methodology to predict the durability and performance of PV panels with solar tracking and fixed topologies. • A solar tracking system stands out as an excellent alternative to maximize PV energy generation. • Detailed technical and economic analysis between performance and durability relationship in a PV panels installation. • Fuzzy logic modeling as an innovative solution to find out the degradation rate of PV panels with solar tracking.

Particle detection and tracking with DNA

We present the first proof-of-concept simulations of detectors using biomaterials to detect particle interactions. The essential idea behind a “DNA detector” involves the attachment of a forest of precisely-sequenced single or double-stranded nucleic acids from a thin holding layer made of a high-density material. Incoming particles break a series of strands along a roughly co-linear chain of interaction sites and the severed segments then fall to a collection area. Since the sequences of base pairs in nucleic acid molecules can be precisely amplified and measured using polymerase chain reaction (PCR), the original spatial position of each broken strand inside the detector can be reconstructed with nm precision. Motivated by the potential use as a low-energy directional particle tracker, we perform the first Monte Carlo simulations of particle interactions inside a DNA detector. We compare the track topology as a function of incoming direction, energy, and particle type for a range of ionising particles. While particle identification and energy reconstruction might be challenging without a significant scale-up, the excellent potential angular and spatial resolution (lesssim 25^circ axial resolution for keV-scale particles and nm-scale track segments) are clear advantages of this concept. We conclude that a DNA detector could be a cost-effective, portable, and powerful new particle detection technology. We outline the outstanding experimental challenges, and suggest directions for future laboratory tests.

Failure analysis of double-row tapered roller bearing outer ring used in Coal Wagon Wheelset

Fatigue fracture took place on a double-row tapered roller bearing outer rings applied in coal loaded train. The fracture is started from one side of the outer ring representing the possible overload condition of the axial or thrust force. The metallurgical investigation includes the hardness test, visual observation, microstructure investigation, and composition. Detailed metallurgical analysis discovered that the defects mainly occurred on the outer ring: (1) the color-changing phenomena might be occurred because of the temperature increase caused by the continuous friction load on the one side of the outer ring raceway, (2) The thermal softening resulting from the continuous load causing decrease in hardness as well as the decrease of the tensile stress. The crack origin is from one side of the bearing and propagate to another side. The thermal softening resulting from possibly continuous applied fatigue and a sudden impact is probably the leading responsible cause of the initial crack. The thermal softening occurrence consequently leads to a decrease in the surface hardness producing low tensile strength. Then, the sudden impact with considerable high force or acceleration caused by the track topology or other factors can cause the initial crack followed by the fracture of the outer ring. In sum, the failure of the bearing is investigated, and the original crack probably occurs because of the high temperature and the axial force overload.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks

Background Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and in situ treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality. We have investigated whether a convolutional neural network (CNN)-based filter is able to improve the image quality. Material and methods The CNN was trained by simulation and reconstruction of tens of millions of proton and helium tracks. The CNN filter was then compared to simple energy loss threshold methods using the Area Under the Receiver Operating Characteristics curve (AUROC), and by comparing the image quality and Water Equivalent Path Length (WEPL) error of proton and helium radiographs filtered with the same methods. Results The CNN method led to a considerable improvement of the AUROC, from 74.3% to 97.5% with protons and from 94.2% to 99.5% with helium. The CNN filtering reduced the WEPL error in the helium radiograph from 1.03 mm to 0.93 mm while no improvement was seen in the CNN filtered pRads. Conclusion The CNN improved the filtering of proton and helium tracks. Only in the helium radiograph did this lead to improved image quality.

Envelope Tracking Power Amplifier Using Short-Time Fourier Transform

A new power amplifier (PA) efficiency enhancement technique using short-time Fourier transform (STFT) in envelope tracking (ET) topology is introduced. The proposed technique produced a time-frequency matrix that illustrated the signal spectrum at each time frame. The applied filter was made time variant by setting a threshold for the preserved power percentage at each time frame. The technique gave full control over the tradeoff between bandwidth (BW) reduction and power consumption efficiency and provided a significant BW reduction over pure ET. The proposed method was demonstrated on a 37 dBm, 40-MHz long-term evolution signal at 2.4 GHz, using 65 W 3-dB compression-point GaN PA. The resulting efficiencies were 38.6% [16-quadrature amplitude modulation (QAM)] and 41.9% (64-QAM).

Single event latch-up detection for nano-satellite external solar radiation mitigation system

This paper presents the single event latch-up (SEL) detection for nano-satellite external solar radiation mitigation system. In this study, the SEL detection analysis was conducted using circuit test and simulation. An electrical power subsystem (EPS) is a part of all CubeSat bus subsystems and it comprises solar arrays, rechargeable batteries, and a power control and distribution unit (PCDU). In order to extract the maximum power generated by the solar arrays, a peak power tracking topology is required. This may lead to the SEL with the presence of high voltage produced by solar. To overcome the SEL problems, the circuit test and simulation must be done so that the flow of SEL will be easily detected and mitigate. The method that been used are by using microcontroller, the SEL will be created in the certain time. The programable integrated circuit (PIC) are used to mitigate SEL effect. It indicates that, the SEL occur very fast in certain time. When the simulation is conducted by using SPENVIS, the result shows, only single event upset (SEU) was affected on UiTMSAT-1.

A numerical implementation of the length-scale independent phase field method

The phase field method for fracture integrates the Griffith theory and damage mechanics approach to predict crack initiation and propagation within one framework. It replaced the discrete representation of crack by diffusive damage and solved it based on a minimization of the global energy storage functional. As a result, no crack tracking topology is needed, and complex crack shapes can be captures without user intervention. However, it is also reported to have an inconsistency between the predicted fracture toughness and the material strength. Recently, a novel energetic degradation function was proposed in literature to handle this issue. This research does some further modifications to the global energy storage functional so that Newton's method can be directly used to solve the energy minimization. With the new energy form, direct implementation of the length-scale independent phase field method into finite element packages like LS-DYNA becomes possible. This paper presents the framework and details of implementing the length-scale independent phase field method into LS-DYNA through a user-defined element and material subroutine. Several numerical examples are presented to compare with the experiment crack shape. Most importantly, this paper is one of the first ones to quantitatively predict accurate force response compared to experiments. These examples verify the accuracy of the new energy form and implementation.

External Topology Tracking Based on State Estimation

A state estimation based approach to obtain an external network equivalent and track topology changes is developed in this work. The proposed approach enables real-time detection and identification of topology-based external events. Following an orthogonal parameter estimator, an index related to the measurement residuals is tracked to detect external disturbances, which are classified based on reference values and actual system data. The method makes use of boundary bus voltages, external currents, an initial snapshot of the network topology, as well as the sensitivity of external changes to the equivalent network. Tests on the IEEE 300-bus and Brazilian 6092-bus systems highlight its capabilities in detecting and identifying shunt, single and double line outages and insertion events.

An Efficient Implementation of Phase Field Method with Explicit Time Integration

The phase field method integrates the Griffith theory and damage mechanics approach to predict crack initiation, propagation, and branching within one framework. No crack tracking topology is needed, and complex crack shapes can be captures without user intervention. In this paper, a detailed description of how the phase field method is implemented with explicit dynamics into LS-DYNA is provided. The displacement field and the damage field are solved in a staggered approach and the phase field equation is solved every Nth time step (N is refered to as calculation cycle) to save computational time. An N value smaller than 1/400 of the total time step numbers is suggested. Several simulations are presented to demonstrate the feasibility of this solving scheme.

Evaluation of a Meandering Track Primary Topology for EV Roadway Charging

Many inductive power transfer dynamic systems have been proposed over the last decade; however, few consider interoperability to various secondaries in the design. This article proposes a limited-length two-phase meandering track primary to investigate the feasibility and tradeoffs between this multicoil track topology and a typical lumped pad primary topology for dynamic applications. The purpose of the proposed track system is to deliver continuous power with a smooth coupling profile which naturally lowers the rating requirements of the secondary electronic components, and to be interoperable with many secondary topologies. The proposed track is compared with a previously published lumped system using double-D primary pads distributed one per meter by a normalized coupling metric. The results show that this meandering track primary has a smaller impact on system electronic components and has better interoperability while it requires lower primary compensation rating compared to the lumped pad primary for the same power level. A prototype of the track was built and the simulation results were verified. A 10 kW power experiment was achieved a dc–dc efficiency of around 83%, and the potential of this multicoil topology for interoperable and low-cost high-power dynamic charging was demonstrated.

Topological background discrimination in the PandaX-III neutrinoless double beta decay experiment

The PandaX-III experiment plans to search for neutrinoless double beta decay (0νββ) of 136Xe in the China JinPing underground Laboratory (CJPL). The experiment will use a high pressure gaseous time projection chamber (TPC) to register both the energy and the electron track topology of an event. This article is devoted to demonstrate our particular detector setup capabilities for the identification of 0νββ and the consequent background reduction. As software tool we use REST, a framework developed for the reconstruction and simulation of TPC-based detector systems. We study the potential for background reduction by introducing appropriate parameters based on the properties of 0νββ events. We exploit for the first time not only the energy density of the electron track-ends, but also the electron scattering angles produced by an electron near the end of its trajectory. To implement this, we have added new algorithms for detector signal and track processing inside REST. Their assessment shows that background can be reduced by about 7 orders of magnitude while keeping 0νββ efficiency above 20% for the PandaX-III baseline readout scheme, a two-dimensional 3 mm pitch stripped readout. More generally, we use the potential of REST to handle 2D/3D data to assess the impact on signal-to-background significance at different detector granularities, and to validate the PandaX-III baseline choice. Finally, we demonstrate the additional potential to discriminate surface background events generated at the readout plane in the absence of t o , by making use of event parameters related with the diffusion of electrons.

New ideas for ring formation and reconstruction in water-Cherenkov detectors

Water-Cherenkov detector technology is well established as is easily seen in the almost identical designs of Kamiokande, Super- and Hyper-Kamiokande. We explore methods to further improve upon their success by extracting directional information from originally lost photons using reflectors placed in the inactive space between PMTs. The reflected photons form a secondary antipodal ring, sensitive to the vertex position and track topology. We further show how ring reconstruction algorithms can benefit from modeling variations of the Cherenkov profile due to showering. Monte Carlo based quantitative estimates are accompanied by discussions of strategies to overcome potential issues with the presented methods. A new CNN-architecture to efficiently implement the cylindrical topology and geometry is also presented.

The NEXT experiment for neutrinoless double beta decay searches

NEXT is an experiment to search for the neutrinoless double beta decay of 136Xe using a high pressure xenon gas time projection chamber. This detector technology has several key advantages, including excellent energy resolution, powerful event classification based on track topology, and favorable mass scalability. The current stage of the experiment, NEXT-White, has been taking data at the Canfranc Underground Laboratory (LSC) in Spain since late 2016. In this talk, we will review recent results from NEXT-White after the first year of low-background operations with both 136Xe-depleted and 136Xe-enriched xenon gas. Background measurements will be shown as well as preliminary results on the two-neutrino mode double beta decay.

Soft-sediment deformation below mammoth tracks at White Sands National Monument (New Mexico) with implications for biomechanical inferences from tracks

Implicit in any biomechanical analysis of tracks (footprints), whatever the animal, is the assumption that depth distribution within the track reflects the applied plantar pressure in some way. Here we describe sub-track deformation structures produced by Proboscidea (probably Mammuthus columbi) at White Sands National Monument (WHSA) in New Mexico. Patterns of sub-surface deformation are consistent with the plantar pressure data for modern Proboscidea, but do not reflect track morphology. Our work cautions against overinterpreting track topology of any large animal, including extinct animals such as sauropods, in terms of their biomechanics unless the subsurface stratigraphy and associated variation in shear strength is known.

Event identification for KM3NeT/ARCA

KM3NeT is a large research infrastructure consisting of a network of deep-sea neutrino telescopes. KM3NeT/ARCA will be the instrument detecting high-energy neutrinos with energies above 100 TeV. This instrument gives a new opportunity to observe the neutrino sky with very high angular resolution to be able to detect neutrino point sources. Furthermore it will be possible to probe the flavour composition of neutrino fluxes, and hence production mechanisms, with so-far unreached precision. Neutrinos produce different event topologies in the detector according to their flavour, interaction channel and deposited energy. Machine-learning algorithms are able to learn features of topologies to discriminate them. In previous analyses only two event types were regarded, namely the shower and track topology. With good timing resolution and precise reconstruction algorithms it is possible to separate into more event types, for example the double bang topology produced by tau neutrinos. The final goal is to distinguish all three neutrino flavors as much as possible. To resolve this issue the KM3NeT collaboration uses deep neural networks trained with Monte Carlo events of all neutrino types. This contribution shows the ability of KM3NeT/ARCA to classify events in more than two neutrino event topologies. Furthermore, the borders between detectable classes are shown, such as the minimum distance the tau has to travel before decaying into a tau neutrino to be detected as double bang event.

Tracking topology structure adaptively with deep neural networks

Object tracking still remains challenging in computer vision because of the severe object variation, e.g., deformation, occlusion, and rotation. To handle the object variation and achieve robust object tracking performance, we propose a novel relationship-based tracking algorithm using neural networks in this paper. Compared with existing approaches in the literature, our method assumes the targeted object to be consisted of several parts and considers the evolution of the topology structure among these parts. After training a candidate neural network for predicting the probable areas each part may locate at in the successive frame, we then design a novel collaboration neural network to determine the precise area each part will locate at with account for the topology structure among these individual parts, which is learned from their historical physical locations during online tracking process. Experimental results show that the proposed method outperforms state-of-the-art trackers on a benchmark dataset, yielding the significant improvements in accuracy on high-distorted sequences.